Multi-Resolution Robot Pathfinding for Large Grid Maps
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Solution Overview
Problem
Existing robot pathfinding methods for large areas with many grids result in increased path search time and memory consumption, leading to decreased travel efficiency and a higher risk of collision with boundaries or obstacles.
Innovation Solution
A grid map-based robot pathfinding method that involves obtaining a first grid map and a second grid map with lower resolution, planning a travel path using the second grid map, determining obstacle positions, and planning transition paths using both grid maps to optimize the robot's path.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robot uses a high-resolution grid map for path planning in large areas, then the path accuracy is improved, but the path search time and memory consumption increase
Solution Approach 1:
The patent divides the grid map into multiple levels of resolution (first grid map with higher resolution and second grid map with lower resolution). The robot first performs path planning on the low-resolution second grid map to obtain a rough path, then refines the path using the high-resolution first grid map only in critical areas. This segmentation approach reduces the overall computational burden while maintaining path accuracy where needed.
Solution Approach 2:
The patent applies different grid resolutions to different regions of the workspace. The first grid map with higher resolution is used for areas requiring precise navigation, while the second grid map with lower resolution is used for areas where approximate positioning suffices. This local quality differentiation optimizes the balance between path accuracy and computational efficiency.
2Measurement precision
If the robot uses a high-resolution grid map for path planning in large areas, then the path accuracy is improved, but the memory consumption increases
Solution Approach 1:
The patent segments the grid map data structure into two levels: a compact low-resolution second grid map for overall path planning and a detailed high-resolution first grid map for local refinement. This segmentation reduces the total memory footprint by storing only essential high-resolution data where needed, rather than maintaining full high-resolution data across the entire large workspace.
Solution Approach 2:
The patent applies high-resolution path planning only partially - specifically, only in regions where the robot requires precise navigation or where obstacles are present. For the majority of the workspace, lower-resolution planning suffices. This partial application of high-resolution processing significantly reduces memory consumption while maintaining adequate path planning accuracy.
3Length of moving object
If the robot follows a path along boundaries or obstacles, then the path length is reduced, but the collision risk increases
Solution Approach 1:
The patent performs preliminary path planning on the low-resolution second grid map to identify potential paths along boundaries or obstacles. Before the robot executes the path, the system refines the path using the high-resolution first grid map to ensure adequate clearance from boundaries and obstacles. This preliminary identification followed by refinement ensures that potentially problematic paths are detected and corrected before execution, reducing collision risk while maintaining path efficiency.
Solution Approach 2:
The patent uses feedback from the high-resolution first grid map to correct and refine the path initially generated from the low-resolution second grid map. When the refined path shows that the robot would be too close to boundaries or obstacles, the system adjusts the path to maintain safe clearance. This feedback mechanism allows the robot to achieve short path lengths while maintaining reliability through continuous path validation and adjustment.
Data Source
AI summary
A grid map-based robot pathfinding method includes obtaining a first grid map and a second grid map, wherein the second grid map is generated by merging grids in the first grid map, and the resolution of the second grid map is lower than that of the first grid map; planning a travel path of a robot from a current position to a preset target point according to the second grid map; and determining an obstacle position if the travel path is impassable, determining a first path of the robot from the current position to the obstacle position based on the second grid map, and determining a second path of the robot from the preset target point to the obstacle position based on the second grid map; planning a transition path from an endpoint of the first path to an endpoint of the second path according to the first grid map; and obtaining a target path of the robot according to the first path, the second path, and the transition path. Related apparatus, robots, and readable non-transitory storage medium are disclosed.